All measured data are fundamentally prone to errors and in many cases the measured data are not consistently available. In addition, the measured data often depend on environmental conditions. Different sensors or sensor systems generally also have different acquisition rates over time, are not synchronized with other sensors or sensor systems and have a latency between the measurement and the output of the measured values. Sensor errors or measurement errors may be broken down into quasi-stationary parts that are constant over multiple measurements, such as, for example, what is referred to as an offset, and statistical parts with a randomness from measurement to measurement, such as noise. While random parts are fundamentally not deterministically correctable, quasi-stationary errors can generally be corrected with a given observability. Uncorrectable significant errors can usually at least be avoided with a given observability.
In this context, sensor fusion methods are already known in the state of the art, which are normally also suitable for correcting or filtering measured data from different sensors or sensor systems. In the automobile industry, in particular, special requirements must also be considered, since a plurality of different sensors capture a common environmental situation or a motor vehicle condition using different measurement principles and describe this environmental situation or this motor vehicle condition by means of a plurality of different measured data. For a sensor fusion that can be used in the automobile industry, therefore, the greatest possible robustness against random faults and detection and compensation of systematic errors is required. The effects of time on the measured data must similarly be corrected and temporary outages or unavailability of sensors bridged.
DE 10 2010 063 984 A1 discloses a sensor system that includes a number of sensor elements. The sensor elements are designed so that they capture, at least to some extent, differing primary measured values and at least to some extent use different measuring principles. From the primary measured values of the sensor elements, at least to some extent, further measured values are then derived. The sensor system also includes a signal processing device, an interface device, and a number of functional devices. Here the sensor elements and all functional devices are connected to the signal processing device. The primary measured values thus provide redundant data which are compared with one another in the signal processing device or are mutually supportive. From the comparison of the observables calculated by a different route, conclusions can be drawn on the reliability and accuracy of the observables. The signal processing device qualifies the accuracy of the observables and provides the observables, together with an indication of their accuracy, via an interface device to various functional devices.
DE 10 2012 216 211 A1 describes a method for selecting a satellite, where the satellite is a satellite of a global navigation system. Before such a satellite is used for determining the position of a vehicle for example, the GNSS signals received are checked for plausibility in various ways. For this verification, different redundancies or known relations are used. Thus, DE 10 2012 216 211 A1, for instance, discloses how to determine, from the signal of a satellite, both the distance of the vehicle to the satellite and also the speed of the vehicle relative to the satellite. Here the distance can be determined by means of the signal traveling time, while the relative speed can be determined by means of a phase measurement of the signal. Since the distance and the relative speed are interdependent, they can be verified against one another. A verification of the values determined from the signal can also be performed against known boundary conditions, since a vehicle usually moves along within a certain speed range. A description is similarly given of how upon receipt of a plurality of signals from various satellites the distances to a number of satellites can be determined and these distances simultaneously verified through trigonometric relationships and the known distance of the satellites from one another. Finally, verification of the distance determined from the signal or the speed determined from the signal by means of other sensors, which similarly allow the determination of a position or the determination of a speed is also possible. Where the signals of a satellite cannot be verified, this satellite is not used for determining the position or for determining the speed.
The generic method and sensor systems known from the state of the art are, however, afflicted with disadvantages in this regard, such that they do not make optimum use of the available redundancies for error detection or mutual verification of the measured values.